Improving Snow‐Process Modeling by Evaluating Reanalysis Vertical Temperature Profiles Using a Distributed Hydrological Model

Abstract

The use of the Japanese 55‐year Reanalysis (JRA55) vertical temperature profile (VTP) has been suggested in previous studies for estimating gridded air temperatures at high elevations in data‐scarce regions to conduct hydrological simulations. In this study, we investigate and further enhance the applicability of VTP for hydrological simulations through several experimental sets using a distributed hydrological model with improved snow physics (WEB‐DHM‐S) based on water and energy budget to simulate the hydrology of a snowfed river basin in Japan, Kurobe Basin, while simultaneously correcting the snow precipitation estimates through optimization. We examined the simulated discharge, point snow depth, and snow cover, finding that the snow processes were highly sensitive to the individual station used with VTP for extrapolating air temperature to higher elevations, with corrected snowfall estimates differing by as much as 18%. We further compared this with simulations based on linear regression‐based lapse rates derived from station observations (scarce and often distributed at low elevations). It was found that the use of VTP improved discharge simulations but deteriorated point snow depth simulations at low elevations, compared with linear regression‐based lapse rates. A hybrid of the two methods led to better discharge and point snow depth simulations with reasonable snow cover simulations. The study advances the application of snow‐process models in data‐scarce regions by enhancing our understanding about the usage of VTP.

Assessing the Sensitivity of Snow Depth Simulations to Land Surface Parameterizations within Noah-MP in Northern Xinjiang, China

“…Land surface models (LSMs) serve as invaluable tools for examining the temporal and spatial dynamics of snow cover. The incorporation of a snow process module into many LSMs and hydrology models has proven effective in achieving satisfactory snow simulation results [16,17]. However, it is noteworthy that LSMs exhibit varying levels of simulation accuracy, with disparities often observed even within the same model across different regions.…”